title: Brain symmetry plane detection based on fractal analysis.
abstract: In neuroimage analysis, the automatic identification of symmetry plane has various applications. Despite the considerable amount of research, this remains an open problem. Most of the existing work based on image intensity is either sensitive to strong noise or not applicable to different imaging modalities. This paper presents a novel approach for identifying symmetry plane in three-dimensional brain magnetic resonance (MR) images based on the concepts of fractal dimension and lacunarity analysis which characterizes the complexity and homogeneity of an object. Experimental results, evaluation, and comparison with two other state-of-the-art techniques show the accuracy and the robustness of our method.
authors.affiliation: School of Information and Communication Technology, Griffith University, Southport, QLD 4222, Australia. Electronic address: surani.jayasuriya@griffithuni.edu.au.
authors.forename: S A
authors.initials: SA
authors.lastname: Jayasuriya
authors.forename: A W C
authors.initials: AW
authors.lastname: Liew
authors.forename: N F
authors.initials: NF
authors.lastname: Law
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D017709:Fractals; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Fractal analysis; Lacunarity; Longitudinal fissure; Mid-sagittal plane; Neuroimaging